By Anup Deb and Steve Kim
TimeMachiNet aims to predict the progression and regression of a person’s face as a function of age, using a machine learning architecture known as a Conditional Adversarial Autoencoder. This application can be used in multiple applications where an age transformation is needed, such as in facial prediction of wanted people, age-invariant verification, recreational use (personal curiosity), or even assisting in the search for missing people.
Check out the report for more technical details about the project.